Demolish MTTR with Autonomous War-Rooms
AegisMCP is an intelligent, multi-agent remediation engine integrated directly with your Splunk MCP server. Write queries, synthesize APM trace logic, and run container patches automatically with secure sandbox verification.
$ aegis-mcp analyze --incident INC-2089
[QueryStrategist] Synthesized Splunk SPL Query:
index=microservices status>=500 | stats count by pod_name, exception
[RootCauseAnalyst] Identified db transaction thread leak inside src/db/pool.py:L42.
[MitigationEngineer] Applied YAML configuration deployment patch to Kubernetes sandbox dry-run environment. Status: PASSED (100% throughput).
Architected for High-Severity Incidents
Reduce MTTR from hours to seconds with specialized LLM Agents targeting your operational runtime.
Splunk MCP Integration
Translates natural user intents into performant Splunk Search Processing Language (SPL) queries directly against schema definitions without table-scans.
Multi-Agent Reasoning
Separate specialized agents handle query formulation, log correlation, dependency modeling, sandbox mitigation design, and Slack/Jira syndication workflows.
Sandboxed Mitigation Dry-Run
Ensures code security. Proposed Kubernetes configs or deployment updates are validated in isolated Docker sandboxes before SRE review and deployment approvals.
Under the Hood
Explore the sequence architecture executing each automated war-room response.
Transforms natural queries to index-safe execution paths
Most SRE operators waste valuable triage minutes searching for logs manually. The QueryStrategist analyzes your historical index schemas dynamically from active Splunk MCP context parameters to limit CPU overhead. It enforces safety boundaries like time limits, preventing massive full-table scan lockups.
Outputs: Optimized executable Splunk SPL query metadata.